The problem of identification of a nonstationary autoregressive process
with unknown, and possibly time-varying, rate of parameter
changes, is considered and solved using the parallel estimation approach.
The proposed two-stage estimation scheme, which combines
the local estimation approach with the basis function one, offers
both quantitative and qualitative improvements compared with
the currently used single-stage methods.